Assessment of uncertainties in damping reduction factors using ANN for acceleration, velocity and displacement spectra


  • Abdelmalek Abdelhamid University of Tissemsilt
  • Baizid Benahmed University of djelfa
  • Mehmet Palanci Istanbul Arel University
  • lakhdar Aidaoui University of djelfa



Damping, Uncertainty, Damping reduction factor, Artificial neural networks, Response spectra


Structure's damping force during an earthquake is very different from what was anticipated during design. This adds uncertainty to the process of designing structures exposed to seismic loads which may be a major cause of significant variation in the seismic response reliability of these structures. This work is focused on the investigation of the structural damping uncertainties effect on the structure’s response spectra through the assessment of uncertainties in the damping reduction factors (DRF) derived from the acceleration, velocity and displacement spectra. An Artificial Neural Networks (ANN) was also developed for the stochastic DRF calculation. The Monte Carlo method, one of the methods of computational algorithms that rely on repeated random sampling to obtain numerical results, is used for the estimation of the stochastic DRF. The obtained results indicates that the difference between the deterministic and the stochastic DRF are around of 21 % for displacement and velocity and 28.7 % for acceleration spectra. As a consequence, the DRF derived from the acceleration spectra is more sensible to the uncertainties inherent on damping than the DRF obtained from displacement and velocity. Therefore, it is important to take this conclusion into account when using these factors previously. The ANN constitutes a sample and efficiency method to predict the stochastic DRF since the error obtained is always less than 6 %. Practice oriented results are searched for, to be incorporated in future seismic standards.


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Baizid, B., & Cardone, D. (2021). ESTIMATION OF STOCHASTIC DAMPING REDUCTION FACTOR USING MONTE CARLO SIMULATION AND ARTIFICIAL NEURAL. Ingegneria Sismica, International Journal of Earthquake Engineering, 04, 37–52.

Benahmed, B. (2018). Formulation of damping reduction factor for the Algerian seismic code. Asian Journal of Civil Engineering, 19(4). DOI:

Benahmed, B., Hammoutene, M., & Cardone, D. (2017). Effects of damping uncertainties on damping reduction factors. Periodica Polytechnica Civil Engineering, 61(2), 341–350. DOI:

Benahmed, B., & Hamoutenne, M. (2018). Use of the Artificial Neural Networks to Estimate the DRF for Eurocode 8. Periodica Polytechnica Civil Engineering, 62(2), 470–479. DOI:

Challagulla, S. P., Bhargav, N. C., & Parimi, C. (2022). Evaluation of damping modification factors for floor response spectra via machine learning model. Structures, 39, 679–690. DOI:

Demir, A., Palanci, M., & Kayhan, A. H. (2020). Evaluation of Supplementary Constraints on Dispersion of EDPs Using Real Ground Motion Record Sets. Arabian Journal for Science and Engineering, 45(10), 8379–8401. DOI:

Fiore, A., & Greco, R. (2020). Influence of Structural Damping Uncertainty on Damping Reduction Factor. Journal of Earthquake Engineering, 00(00), 1–22.

Greco, R., Fiore, A., & Briseghella, B. (2018). Influence of soil type on damping reduction factor: A stochastic analysis based on peak theory. Soil Dynamics and Earthquake Engineering, 104(October 2017), 365–368. DOI:

Hatzigeorgiou, G. D. (2010). Damping modification factors for SDOF systems subjected to near-fault , far-fault and artificial earthquakes. March, 1239–1258. DOI:

Haviland, R. W. (1976). A study of the uncertainties in the fundamental translational periods and damping values for real buildings. Res. Rep. No. 5, Pub. No. R76-12, Dept of Civ. Engng, MIT. Cambridge, MA, 115.

Hiew, S. Y., Teoh, K. Bin, Raman, S. N., Kong, D., & Hafezolghorani, M. (2023). Prediction of ultimate conditions and stress–strain behaviour of steel-confined ultra-high-performance concrete using sequential deep feed-forward neural network modelling strategy. Engineering Structures, 277, 115447. DOI:

Hu, J., Liu, M., & Tan, J. (2022). Damping Modification Factors for Horizontal and Vertical Acceleration Spectra from Offshore Ground Motions in the Japan Sagami Bay Region. Bulletin of the Seismological Society of America, 112(5), 2621–2641. DOI:

Kareem, A. (1988). Aerodynamic response of structures with parametric uncertainties. Structural Safety, 5(3), 205–225. DOI:

Kareem, A., & Gurley, K. (1996). Damping in structures: its evaluation and treatment of uncertainty. Journal of Wind Engineering and Industrial Aerodynamics, 59(2–3), 131–157. DOI:

Kayhan, A. H., Demir, A., & Palanci, M. (2018). Statistical evaluation of maximum displacement demands of SDOF systems by code-compatible nonlinear time history analysis. Soil Dynamics and Earthquake Engineering, 115, 513–530. DOI:

Lin, Y. Y., & Chang, K. C. (2003). Study on Damping Reduction Factor for Buildings under Earthquake Ground Motions. Journal of Structural Engineering, 129(2), 206–214. DOI:

Liu, T., Wang, W., Wang, H., & Su, B. (2021). Improved damping reduction factor models for different response spectra. Engineering Structures, 246, 113012. DOI:

Moustafa, A., & Mahadevan, S. (2011). Reliability analysis of uncertain structures using earthquake response spectra. Earthquakes and Structures, 2(3), 279–295. DOI:

Pennucci, D., Sullivan, T. J., & Calvi, G. M. (2011). Displacement reduction factors for the design of medium and long period structures. Journal of Earthquake Engineering, 15(SUPPL. 1), 1–29. DOI:

Taylor, P., Pennucci, D., Sullivan, T. J., & Calvi, G. M. (n.d.). Displacement Reduction Factors for the Design of Medium and Long Period Structures Displacement Reduction Factors for the Design of Medium and Long Period Structures. December 2014, 37–41.

Zhang, H., & Zhao, Y. G. (2021). Damping Modification Factor of Acceleration Response Spectrum considering Seismological Effects. Journal of Earthquake Engineering, 00(00), 1–24.

Zhang, H., & Zhao, Y. G. (2022). Effects of magnitude and distance on spectral and pseudospectral acceleration proximities for high damping ratio. Bulletin of Earthquake Engineering, 0123456789. DOI:




How to Cite

Abdelhamid, A., Benahmed, B., Palanci , M. and Aidaoui, lakhdar (2023) “Assessment of uncertainties in damping reduction factors using ANN for acceleration, velocity and displacement spectra”, Electronic Journal of Structural Engineering, 23(4), pp. 8–13. doi: 10.56748/ejse.23395.